Challenging Learners in Their Individual Zone of Proximal Development Using Pedagogic Developmental Benchmarks of Syntactic Complexity

Xiaobin Chen
LEAD Graduate School and Research Network, Department of Linguistics, Eberhard Karls Universit¨at T¨ubingen, Germany

Detmar Meurers
LEAD Graduate School and Research Network, Department of Linguistics, Eberhard Karls Universit¨at T¨ubingen, Germany

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Ingår i: Proceedings of the Joint 6th Workshop on NLP for Computer Assisted Language Learning and 2nd Workshop on NLP for Research on Language Acquisition at NoDaLiDa, Gothenburg, 22nd May 2017

Linköping Electronic Conference Proceedings 134:2, s. 8-17

NEALT Proceedings Series 30:2, s. 8-17

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Publicerad: 2017-05-11

ISBN: 978-91-7685-502-7

ISSN: 1650-3686 (tryckt), 1650-3740 (online)


This paper introduces an Intelligent Computer Assisted Language Learning system designed to provide reading input for language learners based on the syntactic complexity of their language production. The system analyzes the linguistic complexity of texts produced by the user and of texts in a pedagogic target language corpus to identify texts that are well-suited to foster acquisition. These texts provide developmental benchmarks offering an individually tailored language challenge, making ideas such as Krashen’s i+1 or Vygotsky’s Zone of Proximal Development concrete and empirically explorable in terms of a broad range of complexity measures in all dimensions of linguistic modeling.


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